US Hospital Service Availability and New 340B Program Participation

Key Points Question Does the US 340B Drug Pricing Program enable participating hospitals to sustain access to hospital-based services and how does hospital ownership affect the influence of 340B participation on hospital service offerings? Findings This longitudinal observational study including 2152 general acute care hospitals found that public hospitals were significantly more likely to sustain unprofitable services after 340B participation, but there was not a meaningful association between 340B participation and service offerings at nonprofit hospitals, except for oncologic services. Meaning These findings suggest that participation in the 340B program enables public but not nonprofit hospitals to sustain unprofitable service lines, such as psychiatric services.


Introduction
The 340B Drug Pricing Program enables participating safety-net hospitals and clinics to receive discounts from pharmaceutical companies on approved outpatient drugs and bill insurers for those drugs at prevailing reimbursement rates.The purpose of the program is to "stretch scarce federal resources as far as possible, reaching more eligible patients and providing more comprehensive services." 1 The discount that covered entities receive is quite large, estimated to be around 35%, 2 and prior research has demonstrated that there is a substantial financial benefit from these discounts. 3e number of hospitals in the program has grown substantially during the past 2 decades, from 591 hospitals in 2005 to 1673 in 2011 4 ; by 2017, there were 2437 hospitals participating. 5By 2021, covered entities spent nearly $44 billion on 340B drugs. 6This growth has been accompanied by increased scrutiny of whether covered entities use the financial benefits to improve access as intended. 4,5though there is clear evidence that 340B participation is associated with improved financial performance of covered entities, there is not a consensus as to whether the financial benefits have been used to subsidize care for patients who have low income and/or are uninsured.][9][10] For example, the provision of uncompensated care and community benefits as a whole were largely unchanged at newly participating hospitals. 7,9,10There is also evidence that hospitals respond to 340B participation by expanding outpatient services that commonly provide high-cost 340B drugs, such as oncologic services. 8,9,11 this study, we extended previous research to evaluate public and nonprofit hospital offerings of relatively unprofitable and profitable services and test whether hospitals respond differently to 340B program participation by ownership or service profitability.8][19] Communities that encounter service line closures are more likely to experience reduced access to care, 20 adverse health outcomes, 21,22 and disruptions in continuity of care, 23 which may widen disparities for groups of patients living in vulnerable situations.Continued provision of these services reflects a hospital's mission to provide safety net services, concordant with the goals of the 340B program.We hypothesized that public hospitals would be more likely to use the financial benefits of 340B program participation to support access to care because they are more likely than nonprofit hospitals to tend to serve patients who have low income and are underinsured.

Methods
This longitudinal cohort study was approved by the University of Arkansas for Medical Science Institutional Review Board and considered exempt because it used only secondary data sources; informed consent was not required for the same reason.We followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cohort studies.

Data Sources
This study used data from the American Hospital Association (AHA) Survey from 2010 to 2019.

Study Sample
The sample included nonprofit and public (state and locally owned) short-term, general, and acute care US hospitals.Most public and nonprofit hospitals are eligible for the 340B program if they maintain a Disproportionate Share Hospital percentage higher than 11.75%. 24For-profit hospitals are not eligible for the 340B program; therefore, they were excluded from the study.The study sample included 2770 short-term general hospitals not participating in the 340B program before 2012.We restricted the study sample to nonparticipating short-term general hospitals to compare newly treated with never treated hospitals, excluding the always treated hospitals, which is an inappropriate comparison group (always and newly treated participant characteristics are presented in eTable 1 in Supplement 1). 25 We excluded 108 hospitals that were missing AHA data on service availability and 181 hospitals that terminated 340B enrollment during the study period.Lastly, we required 340B participating hospitals to report data for at least 1 year before and 1 year after 340B enrollment; thus, hospitals that enrolled in 2019 were excluded from the sample (329 hospitals excluded).The final sample included 2152 hospitals, of which 1074 hospitals began participation from 2012 to 2018, and 1078 hospitals never participated in the 340B program during the study period.

Outcome Measures
We used the approach by Horwitz and Nichols 26,27 to identify profitable and unprofitable clinical services.We included substance use, burn clinics, inpatient psychiatric, outpatient psychiatric, and obstetric services as unprofitable service lines, and cardiac surgery and orthopedic, oncologic, neurologic, and neonatal intensive services as profitable services (AHA definitions are described in the eMethods in Supplement 1).The outcomes included a count of unprofitable and profitable services from 0 to 5, dichotomous indicators for whether any unprofitable or profitable services were provided, and individual service line variables that equal 1 if the hospital directly provided the service.Following the Horwitz approach, we imputed missing service lines if the adjacent observation years were concordant.To confirm that our findings were not due to erroneous reporting in the AHA data, we required hospitals to report at least 2 consistent observation years after a change in service line availability.
Hospital ownership was identified as nonprofit, for-profit, or public, as reported in AHA and validated using Provider of Services files.Other hospital characteristics included the number of patient admissions (<1000, 1000-9999, Ն10 000); hospitals with membership in the Council of Teaching Hospitals; critical access hospital designation; multihospital system status; top quartile of Medicare and Medicaid share, based on the sample distribution; and case-mix index, a weighted measure of admissions by diagnosis-related group reflecting the relative complexity of conditions treated at each hospital.
Hospital market concentration, defined by the Herfindahl-Hirschman Index (HHI) within a Dartmouth Atlas of Health Care Hospital Referral Region (HRR), was included to account for variation in hospital competition.We included for-profit market share, measured by the percentage of discharges from for-profit hospitals in an HRR, because hospital service offerings is dependent on market mix. 26r individual service analyses, we included a control for whether the respective service was offered by a competing hospital in the HRR.Analyses also controlled for county-level demographic and socioeconomic variables, including median household income and percentage of patients who were uninsured, of White race, and age 65 years and older (self-reported data from the American Community Survey).We controlled for the county drug death rate by using the CDC Wide-Ranging Online Data for Epidemiological Research data to adjust for demand of substance use services.A time-varying indicator for whether the state participated in the Affordable Care Act's Medicaid expansion was included using information from the Kaiser Family Foundation. 28Rural hospital was defined as being in a county with a Rural-Urban Area Commuting Code of 4 to 9. 29 We used the SVI to identify hospitals located in socially vulnerable communities. 30SVI is a composite measure based on 15 social factors (eg, socioeconomic, racial and ethnic composition, housing and transportation accessibility) ranging from 0 to 100 with higher scores indicating greater community vulnerability (details provided in the eMethods in Supplement 1).We categorized the SVI variable by terciles.

Statistical Analysis
First, we descriptively compared characteristics between new 340B participants and never participating hospitals by hospital ownership.Bivariate analyses used Student t tests for continuous variables and χ 2 tests for binary variables.Then we estimated difference-in-differences specifications to evaluate how the 340B program affected hospital service line provision.We followed the approach of Callaway and Sant'Anna 31 to account for variation in treatment timing and test the validity of the pretrends.This approach estimated the treatment effect between each treatment cohort (ie, hospitals that began participating at different years) and year, and aggregated these estimates to obtain an average treatment-effect estimate.We also estimated an event study specification within the Callaway and Sant'Anna framework to assess trends before and after 340B participation. 32Primary analyses evaluated all noncritical access hospitals and were stratified by hospital ownership to assess whether public and nonprofit hospitals responded differently to 340B savings.We limited primary analyses to noncritical access hospitals because they typically provide few services and have limited financial flexibility to add services.In subanalyses, we assessed other hospital subgroups that are typically associated with hospital financial performance and community vulnerability.We stratified analyses by geographic location (rural vs urban), community SVI tercile, and critical access designation.
All analyses were based on a linear specification with hospital and calendar year fixed effects.
We controlled for hospital-and market-level characteristics hypothesized to be associated with service availability listed in Table 1.When analyzing all hospitals, we included interaction terms between ownership and rurality, and ownership and SVI categories.The analysis sample included up to 5 years of data before and after 340B participation.Standard errors were clustered at the hospital level.Sensitivity analyses used a balanced panel limited to hospitals that reported in every sample year and logistic regression for dichotomous outcome variables (eTables 2 and 3 in Supplement 1).
We also assessed whether hospitals added or dropped a service line, by stratifying the sample by whether the service was offered at the start of the study period (eTable 4 in Supplement 1).All tests were 2-sided, and statistical significance was defined as P < .05.Analyses were conducted using Stata, version18.0(StataCorp LLC) from January 1, 2023, to January 31, 2024.P < .001).They also served communities with higher percentage of non-Hispanic White populations (82.6% vs 78.0%; P = .007).

Results
Table 2 displays the mean service offerings before and after 340B participation and the unadjusted difference-in-differences estimates.On average, 340B participants offered 1.99 and 1.85 unprofitable services at nonprofit and public hospitals, respectively, before 340B participation.
Program participants generally increased their number of unprofitable services, while control hospitals' services declined.The unadjusted difference-in-differences estimate indicated new 340B hospitals increased total unprofitable services on average by 0.20 (95% CI, 0.11-0.30)and 0.32 (95% CI, 0.07-0.56)at nonprofit and public hospitals, respectively.Program participation was associated with an increase in total profitable services at nonprofit hospitals (0.14; 95% CI, 0.02-0.26),but not public hospitals.Adjusted difference-in-differences analyses estimating the association between 340B participation and service offerings are presented in Table 3. Across all noncritical access hospitals, the 340B program was not associated with unprofitable service offerings, except for a slight increase in obstetrics services by 1.6 (95% CI, 0.1-3.2;P = .04)percentage points (pp).Among nonprofit hospitals, there was no statistically significant change in total or individual unprofitable services.
Among public hospitals, participating in the 340B program was associated with a significant increase in the number of unprofitable services on average by 0.21 (or an 11.4% increase relative to baseline) Abbreviation: D-in-D, difference-in-differences.
a Before and after periods refer to years before and after 340B participation for new participants.The year of 340B participation is excluded as a washout period.
b For never-340B participants, the before and after periods represent years 2010 to 2011 and 2018 to 2019, respectively.
c Difference column refers to the before and after period differences.
d Unadjusted difference-in-differences estimate refers to the differential change in service offerings in the after period relative to the before period treatment-control difference.
e 95% CIs were calculated using standard errors clustered at the hospital level.
The statistics represent the proportion of hospitals offering the service, except for the total number of profitable or unprofitable services which represent the mean.The sample comprises noncritical access hospitals.
compared with public hospitals that did not participate in the program (95% CI, 0.04-0.38;P = .02).
Public hospitals were also associated with a marginally significant increase in substance use and inpatient psychiatric services (P < .10).Among nonprofit hospitals, the 340B program was significantly associated with an increase in oncologic services by 2.5 (95% CI, 0.0-5.0;P = .05)pp, while public hospitals' profitable services were unaffected.The results were overall robust to sensitivity analyses using a balanced panel and logistic regression (eTables 3 and 4 in Supplement 1).
b 95% CIs are calculated using standard errors clustered at the hospital level.

Discussion
We found that public hospitals newly participating in the 340B program from 2012 to 2018 were more likely to expand unprofitable service line offerings compared with public hospitals that never participated.However, service provisions at nonprofit hospitals were largely unaffected by the 340B program, except for an increase in oncologic service offerings.Public hospitals were associated with a marginally significant increase in both substance use and inpatient psychiatric services.These findings are notable given concerns regarding service closure across the US, 22,33 and the increasing trends in substance use disorders and mental health conditions. 34,35ese findings suggest that 340B participation may enable public hospitals to sustain unprofitable, yet essential services.This finding is concordant with the underlying mission of the 340B program to subsidize comprehensive services for patients who need safety net services.We interpret these findings as reflecting cross-subsidization of unprofitable service lines indicating that the financial benefits of 340B participation were used to support access, regardless of the extent to which a service line received 340B savings.This is consistent with prior evidence suggesting that hospitals reduced the provision of psychiatric and substance use services in association with a decline in the profitability of cardiac services. 36In this case, 340B participation likely lowered the pharmaceutical cost of services that were reliant on hospital-based therapeutics, and the financial benefits were then used to sustain unprofitable service lines at public hospitals.Although we found that the 340B program was associated with an increase in services at public hospitals, there was no meaningful change in unprofitable service provisions at nonprofit hospitals.
This evidence is consistent with several past studies that found no association between hospital 340B program participation and improved access to safety net services. 7,8,10The finding persisted when stratifying our sample by geographic area, SVI, and critical access hospital designation, indicating that nonprofit hospitals located in socially vulnerable areas were not more likely to provide unprofitable services after 340B participation despite a possibly high need.Given that the US is reliant on hospitals to provide safety net services to patients who have low income and are uninsured, 37 sustaining access to services is needed to improve population health and reduce disparities in outcomes.

Limitations
First, there are important differences between hospitals that qualify for the 340B program and those that do not.Although we attempted to control for several hospital and market-level confounders, selection bias may remain.The comparison group included hospitals that do not qualify for 340B participation due either to payer mix or unmeasured management quality.There is also evidence that some hospitals manipulate their Disproportionate Share Hospital percentage to become eligible for the 340B program. 38Furthermore, the number of public hospitals in the sample is limited and the analyses may have been underpowered in some cases.a Displays the coefficient from the difference-in-differences estimate using ordinary least squares regression adjusted for control variables in Hospital service availability was identified using AHA data.The Health Resources and Services Administration Office of Pharmacy Affairs Information System 340B covered entity daily report was used to identify 340B participating hospitals and participation dates.The Centers for Medicare & Medicaid Services Hospital Cost Report Information System and Provider of Services files were used to obtain additional hospital characteristics.We obtained market-level characteristics from the Agency for Healthcare Research and Quality Social Determinants of Health Database.This dataset compiles demographic, socioeconomic, and health variables from several sources.We used variables from the American Community Survey and the US Centers for Disease Control and Prevention (CDC) Wide-Ranging Online Data for Epidemiological Research and the Social Vulnerability Index (SVI).Demographic information including race and ethnicity was self-reported.

Table 1 .
Baseline Hospital and Market Characteristics for Hospitals Never Participating in the 340B Program and Newly Participating Hospitals in 2012 to 2018, by Hospital Ownership a a Hospitals' first observation year in the dataset was used.The 340B column represents hospitals that began participating in the 340B program from 2012 to 2018.The comparison hospitals represent those that never participated in the program throughout the study period.The P value indicates the difference between new participating hospitals and never 340B hospitals using Student t tests for continuous and χ 2 tests for binary variables.bMedian annual household income is standardized by $1000.

Table 2 .
Unadjusted Service Provisions Before and After New Hospital 340B Program Participation From 2012 to 2018 Compared With Never Participating Hospitals

Table 3 .
Difference-in-Differences Estimates of Service Provisions for Hospitals Newly Participating in the 340B Program Compared With Never Participating, by Hospital Ownership

Table 4 .
Difference-in-Differences Estimates of Service Provisions for Hospitals Newly Participating in the 340B Program Compared With Never Participating Hospitals, by Community Social Vulnerability Index, and Critical Access Designation Table 1 and with hospital and calendar year fixed effects.Results account for staggered entry into the 340B program.This paper was presented at the American Society of Health Economists Annual Conference; June 11 to 14, 2023; St Louis, Missouri; and the AcademyHealth Annual Research Meeting; June 24 to 27, 2023; Seattle, Washington.SUPPLEMENT 1. eMethods 1.American Hospital Association (AHA) Survey Services Definitions eMethods 2. Centers for Disease Control and Prevention Social Vulnerability Index Measure eMethods 3. Model Specification eTable 1. Baseline Hospital and Market Characteristics by New vs Always 340B Participation and Hospital Ownership eTable 2. Difference-in-Differences Estimates of Service Provisions Using a Balanced Panel eTable 3. Difference-in-Differences Estimates Using Logistic Regression eTable 4. Difference-in-Differences Estimates by Whether Hospital Offered Service at Start of the Study Period eReferences b 95% CIs are calculated using standard errors clustered at the hospital level.cThirty-onehospitals were missing Social Vulnerability Index data.Meeting Presentations: